Application Exercise

1. Open Rstudio Server Pro
2. Create a new project
3. Click File > New File > R Markdown
4. Delete everything except for

---
title: "Untitled"
output: html_document
---

5. Give your work a sensible title
6. When you’ve finished, upload the .html file to Canvas

• Fit a linear model using the mtcars data frame predicting miles per gallon (mpg) from (wt)
• Pull out the coefficients and confidence intervals using the tidy() function demonstrated. How do you interpret these?
• Using the linear model you fit previously (mpg from wt using the mtcars data) - calculate the p-value for the coefficient for weight? Interpret this value. What is the null hypothesis? What is the alternative hypothesis? Do you reject the null?
• Using the model previously fit (using the mtcars data predicting miles per gallon from weight), pull out the F-statistic and \(R^2\) using the glance() function. Interpret these values.

Below is some code to get you started:

library(tidymodels)
library(tidyverse)